1,721,245 research outputs found
La valutazione strumentale dell'equilibrio e della postura nel paziente con neuropatia diabetica
No full textSignal Processing in Movement Analysis (a state-space approach)
No full textSignalprocessing techniques in movementanalysis (MA) are a pre-requisite for further processing of MA data and can heavily affect the reliability of these latter results. In this paper, a brief review of classical digital signalprocessing techniques used in MA will be outlined, but emphasis will be given to a particular class of methods based on the state-spaceapproach and in particular on the application of Kalman filtering theory. It will be shown the use of these techniques for the solution of linear and non-linear filtering problems such as those, respectively, relative to the numerical smoothing/differentiation of noisy signals and relative to the filtering of multiple displacement data subject to kinematic constraints
Opimal Estimation of a Rigid Body Pose
No full textA typical movement analysis problem is the estimation, at every time instant, of the position vector k and of the orientation matrix R describing the pose of a segment, supposed rigid, based on the position measurement of N points embedded with the segment. The orthonormal matrix R and the k-vector have to satisfy the following co-ordinate transformation pi,true=R ai,true + k where pi,true and ai,true are the error-free i-th point co-ordinates in the fixed and moving frame, respectively. Defining as l=[a1T p1 T,...,aN T pN T] T the vector of observations affected by additive white noise, as the optimal estimate of l, and as Q-1 a suitable weight matrix, in this paper, the optimal estimate of R, k, (and l) is obtained considering both pi and ai as noisy observations by iteratively minimization, in the least squares sense, of the following functional = ( l )TQ-1( l ), looking for the solution that satisfies the co-ordinate transformation. At every iteration, adjustment is performed both on parameters (R and k) and on observations. Results are compared with those obtained by Singular Value Decomposition (SVD) [1] and by the method proposed in [2]
Three-dimensional in-vivo kinematic analysis of finger movement
No full textF.Schuind, K.N. An, W.P. Cooney III, M. Garcia-Elias Editor
Assessment of clinical protocols, a summary of two days workshop held at Ancona University , October 16-17, 1989
No full textKinematic characterization of standing reach: A markerless approach
No full textFalls in the elderly represent a leading cause of
disability, injury, and death. Identification of elderly people at high
risk of falling should be a leadingmedical priority. In literature there
are many clinical balance tests used to predict falls. The motor task
taken into account in this work is the standing reach (SR) [1].
The SR consists in leaning the trunk forward trying to reach the
maximum displacement of the arms, and maintaining the wrists
at approximately the same height during the whole movement.
The base of support is fixed during the task because the subject
is required not to lift his heels or step forward. The maximum
displacement of the hands (handmax) is a measure of clinical significance for its predictive value about recurrent falls in the elderly
subjects. Nevertheless, only this measure, cannot be considered a
measure of dynamic balance, in the sense that it is not able to differentiate healthy elders from individuals with balance impairments.
More insight can be obtained from the same motor task if it can be
described looking also at its kinematic behaviour. The aim of this work was to derive a procedure able to estimate joint kinematics and the centre of mass (CoM) excursion during SR test, using a
markerless approach and computer graphic methods
- …
